scholarly journals Implications of North Atlantic Sea Surface Salinity for Summer Precipitation over the U.S. Midwest: Mechanisms and Predictive Value

2016 ◽  
Vol 29 (9) ◽  
pp. 3143-3159 ◽  
Author(s):  
Laifang Li ◽  
Raymond W. Schmitt ◽  
Caroline C. Ummenhofer ◽  
Kristopher B. Karnauskas

Abstract Moisture originating from the subtropical North Atlantic feeds precipitation throughout the Western Hemisphere. This ocean-to-land moisture transport leaves its imprint on sea surface salinity (SSS), enabling SSS over the subtropical oceans to be used as an indicator of terrestrial precipitation. This study demonstrates that springtime SSS over the northwestern portion of the subtropical North Atlantic significantly correlates with summertime precipitation over the U.S. Midwest. The linkage between springtime SSS and the Midwest summer precipitation is established through ocean-to-land moisture transport followed by a soil moisture feedback over the southern United States. In the spring, high SSS over the northwestern subtropical Atlantic coincides with a local increase in moisture flux divergence. The moisture flux is then directed toward and converges over the southern United States, which experiences increased precipitation and soil moisture. The increased soil moisture influences the regional water cycle both thermodynamically and dynamically, leading to excessive summer precipitation in the Midwest. Thermodynamically, the increased soil moisture tends to moisten the lower troposphere and enhances the meridional humidity gradient north of 36°N. Thus, more moisture will be transported and converged into the Midwest by the climatological low-level wind. Dynamically, the increases in soil moisture over the southern United States enhance the west–east soil moisture gradient eastward of the Rocky Mountains, which can help to intensify the Great Plains low-level jet in the summer, converging more moisture into the Midwest. Owing to these robust physical linkages, the springtime SSS outweighs the leading SST modes in predicting the Midwest summer precipitation and significantly improves rainfall prediction in this region.

2013 ◽  
Vol 26 (4) ◽  
pp. 1249-1267 ◽  
Author(s):  
Chunzai Wang ◽  
Liping Zhang ◽  
Sang-Ki Lee

Abstract The response of freshwater flux and sea surface salinity (SSS) to the Atlantic warm pool (AWP) variations from seasonal to multidecadal time scales is investigated by using various reanalysis products and observations. All of the datasets show a consistent response for all time scales: A large (small) AWP is associated with a local freshwater gain (loss) to the ocean, less (more) moisture transport across Central America, and a local low (high) SSS. The moisture budget analysis demonstrates that the freshwater change is dominated by the atmospheric mean circulation dynamics, while the effect of thermodynamics is of secondary importance. Further decomposition points out that the contribution of the mean circulation dynamics primarily arises from its divergent part, which mainly reflects the wind divergent change in the low level as a result of SST change. In association with a large (small) AWP, warmer (colder) than normal SST over the tropical North Atlantic can induce anomalous low-level convergence (divergence), which favors anomalous ascent (decent) and thus generates more (less) precipitation. On the other hand, a large (small) AWP weakens (strengthens) the trade wind and its associated westward moisture transport to the eastern North Pacific across Central America, which also favors more (less) moisture residing in the Atlantic and hence more (less) precipitation. The results imply that variability of freshwater flux and ocean salinity in the North Atlantic associated with the AWP may have the potential to affect the Atlantic meridional overturning circulation.


2007 ◽  
Vol 24 (2) ◽  
pp. 255-269 ◽  
Author(s):  
Sabine Philipps ◽  
Christine Boone ◽  
Estelle Obligis

Abstract Soil Moisture and Ocean Salinity (SMOS) was chosen as the European Space Agency’s second Earth Explorer Opportunity mission. One of the objectives is to retrieve sea surface salinity (SSS) from measured brightness temperatures (TBs) at L band with a precision of 0.2 practical salinity units (psu) with averages taken over 200 km by 200 km areas and 10 days [as suggested in the requirements of the Global Ocean Data Assimilation Experiment (GODAE)]. The retrieval is performed here by an inverse model and additional information of auxiliary SSS, sea surface temperature (SST), and wind speed (W). A sensitivity study is done to observe the influence of the TBs and auxiliary data on the SSS retrieval. The key role of TB and W accuracy on SSS retrieval is verified. Retrieval is then done over the Atlantic for two cases. In case A, auxiliary data are simulated from two model outputs by adding white noise. The more realistic case B uses independent databases for reference and auxiliary ocean parameters. For these cases, the RMS error of retrieved SSS on pixel scale is around 1 psu (1.2 for case B). Averaging over GODAE scales reduces the SSS error by a factor of 12 (4 for case B). The weaker error reduction in case B is most likely due to the correlation of errors in auxiliary data. This study shows that SSS retrieval will be very sensitive to errors on auxiliary data. Specific efforts should be devoted to improving the quality of auxiliary data.


2018 ◽  
Vol 10 (8) ◽  
pp. 1232 ◽  
Author(s):  
Semyon Grodsky ◽  
Douglas Vandemark ◽  
Hui Feng

Monitoring the cold and productive waters of the Gulf of Maine and their interactions with the nearby northwestern (NW) Atlantic shelf is important but challenging. Although remotely sensed sea surface temperature (SST), ocean color, and sea level have become routine, much of the water exchange physics is reflected in salinity fields. The recent invention of satellite salinity sensors, including the Soil Moisture Active Passive (SMAP) radiometer, opens new prospects in regional shelf studies. However, local sea surface salinity (SSS) retrieval is challenging due to both cold SST limiting salinity sensor sensitivity and proximity to land. For the NW Atlantic, our analysis shows that SMAP SSS is subject to an SST-dependent bias that is negative and amplifies in winter and early spring due to the SST-related drop in SMAP sensor sensitivity. On top of that, SMAP SSS is subject to a land contamination bias. The latter bias becomes noticeable and negative when the antenna land contamination factor (LC) exceeds 0.2%, and attains maximum negative values at LC = 0.4%. Coastward of LC = 0.5%, a significant positive land contamination bias in absolute SMAP SSS is evident. SST and land contamination bias components are seasonally dependent due to seasonal changes in SST/winds and terrestrial microwave properties. Fortunately, it is shown that SSS anomalies computed relative to a satellite SSS climatology can effectively remove such seasonal biases along with the real seasonal cycle. SMAP monthly SSS anomalies have sufficient accuracy and applicability to extend nearer to the coasts. They are used to examine the Gulf of Maine water inflow, which displayed important water intrusions in between Georges Banks and Nova Scotia in the winters of 2016/17 and 2017/18. Water intrusion patterns observed by SMAP are generally consistent with independent measurements from the European Soil Moisture Ocean Salinity (SMOS) mission. Circulation dynamics related to the 2016/2017 period and enhanced wind-driven Scotian Shelf transport into the Gulf of Maine are discussed.


2019 ◽  
Vol 11 (15) ◽  
pp. 1818 ◽  
Author(s):  
Daniele Ciani ◽  
Rosalia Santoleri ◽  
Gian Luigi Liberti ◽  
Catherine Prigent ◽  
Craig Donlon ◽  
...  

We present a study on the potential of the Copernicus Imaging Microwave Radiometer (CIMR) mission for the global monitoring of Sea-Surface Salinity (SSS) using Level-4 (gap-free) analysis processing. Space-based SSS are currently provided by the Soil Moisture and Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) satellites. However, there are no planned missions to guarantee continuity in the remote SSS measurements for the near future. The CIMR mission is in a preparatory phase with an expected launch in 2026. CIMR is focused on the provision of global coverage, high resolution sea-surface temperature (SST), SSS and sea-ice concentration observations. In this paper, we evaluate the mission impact within the Copernicus Marine Environment Monitoring Service (CMEMS) SSS processing chain. The CMEMS SSS operational products are based on a combination of in situ and satellite (SMOS) SSS and high-resolution SST information through a multivariate optimal interpolation. We demonstrate the potential of CIMR within the CMEMS SSS operational production after the SMOS era. For this purpose, we implemented an Observing System Simulation Experiment (OSSE) based on the CMEMS MERCATOR global operational model. The MERCATOR SSSs were used to generate synthetic in situ and CIMR SSS and, at the same time, they provided a reference gap-free SSS field. Using the optimal interpolation algorithm, we demonstrated that the combined use of in situ and CIMR observations improves the global SSS retrieval compared to a processing where only in situ observations are ingested. The improvements are observed in the 60% and 70% of the global ocean surface for the reconstruction of the SSS and of the SSS spatial gradients, respectively. Moreover, the study highlights the CIMR-based salinity patterns are more accurate both in the open ocean and in coastal areas. We conclude that CIMR can guarantee continuity for accurate monitoring of the ocean surface salinity from space.


2019 ◽  
Vol 53 (9-10) ◽  
pp. 5495-5509 ◽  
Author(s):  
Lili Zeng ◽  
Raymond W. Schmitt ◽  
Laifang Li ◽  
Qiang Wang ◽  
Dongxiao Wang

2020 ◽  
Author(s):  
Audrey Hasson ◽  
Cori Pegliasco ◽  
Jacqueline Boutin ◽  
Rosemary Morrow

<p>Since 2010, space missions dedicated to Sea Surface Salinity (SSS) have been providing observations with almost complete coverage of the global ocean and a resolution of about 45 km every 3 days. The European Space Agency (ESA) Soil Moisture and Ocean Salinity (SMOS) mission was the first orbiting radiometer to collect regular SSS observations from space. The Aquarius and SMAP (Soil Moisture Active-Passive) missions of the National Aeronautics and Space Administration (NASA) then reinforced the SSS observing system between mid-2011 and mid-2015 and since mid-2015, respectively.</p><p>Using the most recent SSS Climate Change Initiative project dataset merging data from the 3 missions, this study investigates the SSS signal associated with mesoscale eddies in the Southern Ocean. Eddies location and characteristics are obtained from the daily v3 mesoscale eddy trajectory atlas produced by CLS. SSS anomalies along the eddies journey are computed and compared to Sea Surface Temperature (SST) anomalies (v4 Remote Sensing Systems) as well as the SubAntarctic Front (SAF) position (CTOH, LEGOS). The vertical structure of the eddies is further investigated using profiles from colocated Argo autonomous floats.<span> </span></p><p>This study highlights a robust signal in SSS depending on both the eddies rotation (cyclone/anticyclone) and latitudinal position with respect to the SAF. Moreover, this dependence is not found in SST. These observations reveal oceanic the interaction of eddies with the larger scale ocean water masses. SSS and SST anomalies composites indeed show different patterns either bi-poles linked with horizontal stirring of fronts, mono-poles from trapping water or vertical mixing changes, or a mix of the two.</p><p>This analysis gives strong hints for the erosion of subsurface waters, such as mode waters, induced by enhanced mixing caused by the deep-reaching eddies of the southern ocean.</p>


2020 ◽  
Author(s):  
Sisi Qin

<p>In this study, Sea Surface Salinity (SSS) Level 3 (L3) daily product derived from Soil Moisture Active Passive (SMAP) during the year 2016, was validated and compared with SSS daily products derived from Soil Moisture and Ocean Salinity (SMOS) and in-situ measurements. Generally, the Root Mean Square Error (RMSE) of the daily SSS products is larger along the coastal areas and at high latitudes and is smaller in the tropical regions and open oceans. Comparisons between the two types of daily satellite SSS product revealed that the RMSE was higher in the daily SMOS product than in the SMAP, whereas the bias of the daily SMOS was observed to be less than that of the SMAP when compared with Argo floats data. In addition, the latitude-dependent bias and RMSE of the SMAP SSS were found to be primarily influenced by the precipitation and the Sea Surface Temperature (SST).Then, aregression analysis method which has adopted the precipitation and SST data was used to correct the larger bias of the daily SMAP product. It was confirmed that the corrected daily SMAP product could be used for assimilation in high-resolution forecast models, due to the fact that it was demonstrated to be unbiased and much closer to the in-situ measurements than the original uncorrected SMAP product.</p>


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